1. Field of the Invention
The present invention relates to an image processing method for correcting an input image signal using a spatial filter to sharpen blurred images.
2. Description of the Prior Art
It is known that the MTF (modulation transfer function) drops and image blurring occurs in digital photocopiers, facsimile machines, and other document readers because of the spatial frequency characteristics of the lens and other optical system components and the CCD and other photoelectric conversion sensors.
Image blurring occurs because the spatial frequency characteristics of the optical system and sensors attenuate high frequency components greater than low frequency components. Conventionally, this image blurring has been corrected by enhancing the high frequency component of the image to effectively sharpen the image. This is achieved by applying a spatial filtering process called a Laplacian filter using the Laplacian component, which is the quadratic differential of the image, correcting MTF deterioration, and thus sharpening the playback image.
This Laplacian filtering process is described below, and the Laplacian principle is illustrated in FIG. 15.
In FIG. 15, the target pixel signal is D(i,j), and the reference pixel signals in the four directions surrounding the target pixel are D(i,j-1), D(i-1,j), D(i+1,j), and D(i,j+1). The corrected signal D'(i,j) after Laplacian filtering is expressed by equation [1]. EQU D'(i,j)=D(i,j)+a .gradient..sup.2 D [1]
where "a" is a constant and EQU .gradient..sup.2 D=4.times.D(i,j)-{D(i,j-1)+D(i-1,j)+D(i+1,j)+D(i,j+1)}
As the equations illustrate, this correction is achieved by adding the difference between the target pixel signal and the sum of the four reference pixel signals on the four sides of the target pixel to the target pixel signal.
In general, correcting the MTF by means of Laplacian filtering also enhances the noise in the picture, resulting in a grainy image with a decreased S/N ratio. To avoid this, a dead zone wherein the constant "a" is defined as zero (0) is provided to prevent image enhancement when the Laplacian operator .gradient..sup.2 D in the equation [1] is less than a predetermined threshold value.
An edge enhancement method is known (Japanese patent laid-open publication No. #SHO 63-3562) whereby each signal difference between a target pixel and a reference pixel is obtained, the image edge is detected using these differences, and enhancement is applied only in the direction of the image edge by switching the table of interpolation coefficients according to the detection result so that isolated noise components with no correlation to the edge pixel are not enhanced.
However, while the effects of noise are not included in the corrected signal when the level of noise in the image is less than the predetermined threshold value in this Laplacian filtering process, noise is also enhanced when the noise level exceeds this threshold value. Conversely, when the Laplacian operator .gradient..sup.2 D is less than the threshold value, even contour lines that should be enhanced are not properly enhanced.
Furthermore, while an edge enhancement method which changes the table of interpolation coefficients according to the result of a correlation detection has been proposed, detection of diagonal lines in an image, and particularly edge lines with an acute angle slope, is difficult. When detection errors occur and these diagonal lines are not detected, diagonal lines assume a jagged line on a display screen.
In addition, interference such as crossed colors and dot interference in the current NTSC (National Television System Committee) television system format causes a signal representing a straight line to be reproduced as a jagged line of single offset pixels. Applying Laplacian filtering to this jagged line simply results in an enhanced jagged line rather than the original straight line, and a corresponding deterioration of image quality.
Video printers which produce a hard-copy printout of the video signal are now commercially available. These video printers record the number of pixels corresponding to one television signal frame. When the input signal is a moving image, however, there is motion between the two fields forming a single frame. The field signals are therefore digitized, and the digitized field signals are interpolated to obtain the total number of pixels forming a single frame signal.
Application of this conventional Laplacian filtering process to the interpolated signal, however, cancels the effects of interpolation and loses the smoothness interpolated into diagonal lines.